Lazy Abstraction-Based Controller Synthesis

We present lazy abstraction-based controller synthesis (ABCS) for continuous-time nonlinear dynamical systems against reach-avoid and safety specifications. State-of-the-art multi-layered ABCS pre-computes multiple finite-state abstractions of varying granularity and applies reactive synthesis to the coarsest abstraction whenever feasible, but adaptively considers finer abstractions when necessary. Lazy ABCS improves this technique by constructing abstractions on demand. Our insight is that the abstract transition relation only needs to be locally computed for a small set of frontier states at the precision currently required by the synthesis algorithm. We show that lazy ABCS can significantly outperform previous multi-layered ABCS algorithms: on standard benchmarks, lazy ABCS is more than 4 times faster

Lazy transition systems and asynchronous circuit synthesis with relative timing assumptions

Journal ArticleThis paper presents a design flow for timed asynchronous circuits. It introduces lazy transitions systems as a new computational model to represent the timing information required for synthesis. The notion of laziness explicitly distinguishes between the enabling and the firing of an event in a transition system. Lazy transition systems can be effectively used to model the behavior of asynchronous circuits in which relative timing assumptions can be made on the occurrence of events. These assumptions can be derived from the information known a priori about the delay of the environment and the timing characteristics of the gates that will implement the circuit. The paper presents necessary conditions to generate circuits and a synthesis algorithm that exploits the timing assumptions for optimization. It also proposes a method for back-annotation that derives a set of sufficient timing constraints that guarantee the correctness of the circuit

How to Handle Assumptions in Synthesis

The increased interest in reactive synthesis over the last decade has led to many improved solutions but also to many new questions. In this paper, we discuss the question of how to deal with assumptions on environment behavior. We present four goals that we think should be met and review several different possibilities that have been proposed. We argue that each of them falls short in at least one aspect.Comment: In Proceedings SYNT 2014, arXiv:1407.493

A Finite State and Data-Oriented Method for Grapheme to Phoneme Conversion

A finite-state method, based on leftmost longest-match replacement, is presented for segmenting words into graphemes, and for converting graphemes into phonemes. A small set of hand-crafted conversion rules for Dutch achieves a phoneme accuracy of over 93%. The accuracy of the system is further improved by using transformation-based learning. The phoneme accuracy of the best system (using a large set of rule templates and a `lazy' variant of Brill's algoritm), trained on only 40K words, reaches 99% accuracy.Comment: 8 page

Lazy Security Controllers

A security controller follows the execution of a target to identify and prevent security violations. Eective controllers proactively observe a full execution of a target and, in case of a security violation, either interrupt or modify its original behaviour. Beyond the theoretical aspects, the assumption that a controller can observe the entire execution of its target might be restrictive in several practical cases. In this paper we dene lazy controllers, a category of security controllers which can schedule observation points over the target execution. Finding an optimal scheduling strategy is non-trivial in general. Indeed, a lazy controller could miss security-sensitive observations. Also, we propose synthesis strategies applicable to (i) non-deterministic targets with non-instantaneous actions, (ii) probabilistic targets modelled as Discrete Time Markov Chains and (iii) stochastic targets modelled as Continuous Time Markov Chains. In each case we give an analytical characterization of the probability that the lazy controller misses the detection of a violation

Specific "scientific" data structures, and their processing

Programming physicists use, as all programmers, arrays, lists, tuples, records, etc., and this requires some change in their thought patterns while converting their formulae into some code, since the "data structures" operated upon, while elaborating some theory and its consequences, are rather: power series and Pad\'e approximants, differential forms and other instances of differential algebras, functionals (for the variational calculus), trajectories (solutions of differential equations), Young diagrams and Feynman graphs, etc. Such data is often used in a [semi-]numerical setting, not necessarily "symbolic", appropriate for the computer algebra packages. Modules adapted to such data may be "just libraries", but often they become specific, embedded sub-languages, typically mapped into object-oriented frameworks, with overloaded mathematical operations. Here we present a functional approach to this philosophy. We show how the usage of Haskell datatypes and - fundamental for our tutorial - the application of lazy evaluation makes it possible to operate upon such data (in particular: the "infinite" sequences) in a natural and comfortable manner.Comment: In Proceedings DSL 2011, arXiv:1109.032

Modeling and Simulation of Elementary Robot Behaviors using Associative Memories

International audienceToday, there are several drawbacks that impede the necessary and much needed use of robot learning techniques in real applications. First, the time needed to achieve the synthesis of any behavior is prohibitive. Second, the robot behavior during the learning phase is – by definition – bad, it may even be dangerous. Third, except within the lazy learning approach, a new behavior implies a new learning phase. We propose in this paper to use associative memories (self-organizing maps) to encode the non explicit model of the robot-world interaction sampled by the lazy memory, and then generate a robot behavior by means of situations to be achieved, i.e., points on the self-organizing maps. Any behavior can instantaneously be synthesized by the definition of a goal situation. Its performance will be minimal (not necessarily bad) and will improve by the mere repetition of the behavior

Highly Scalable Algorithms for Robust String Barcoding

String barcoding is a recently introduced technique for genomic-based identification of microorganisms. In this paper we describe the engineering of highly scalable algorithms for robust string barcoding. Our methods enable distinguisher selection based on whole genomic sequences of hundreds of microorganisms of up to bacterial size on a well-equipped workstation, and can be easily parallelized to further extend the applicability range to thousands of bacterial size genomes. Experimental results on both randomly generated and NCBI genomic data show that whole-genome based selection results in a number of distinguishers nearly matching the information theoretic lower bounds for the problem